Physiological phantoms incorporating feedback sensors and sensing materials

ABSTRACT

Disclosed herein are physiological phantoms incorporating sensors and sensor materials integrated with a tissue phantom of an anatomical part. The sensors and sensor materials include small diameter optical fibers containing Bragg gratings, thermochromic materials, electrical strain gauges, flexible strain gauges, shape sensing cables, electrochromic materials and etc. The sensors and sensing materials may mimic tissue as part of the tissue phantom. They may mimic the directionality, density, elasticity of the anatomical tissues they may be mimicking. The sensors and sensing materials may be sensitive to strain, heat, electricity, shape, light, and etc. similar to what may occur during medical procedures using various medical devices and tools such as a scalpel, a needle, a deep brain stimulation probe, a port used in brain or spinal surgery and etc.

FIELD

The present disclosure relates to sensorized medical, imaging andsurgical training phantoms.

BACKGROUND

In the field of medicine, imaging and image guidance are a significantcomponent of clinical care. From diagnosis and monitoring of disease, toplanning of the surgical approach, to guidance during procedures andfollow-up after the procedure is complete, imaging and image guidanceprovides effective and multifaceted treatment approaches, for a varietyof procedures, including surgery and radiation therapy. Targeted stemcell delivery, adaptive chemotherapy regimes, and radiation therapy areonly a few examples of procedures utilizing imaging guidance in themedical field.

Advanced imaging modalities such as Magnetic Resonance Imaging (“MRI”)have led to improved rates and accuracy of detection, diagnosis andstaging in several fields of medicine including neurology, where imagingof diseases such as brain cancer, stroke, Intra-Cerebral Hemorrhage(“ICH”), and neurodegenerative diseases, such as Parkinson's andAlzheimer's, are performed. As an imaging modality, MRI enablesthree-dimensional visualization of tissue with high contrast in softtissue without the use of ionizing radiation. This modality is oftenused in conjunction with other modalities such as Ultrasound (“US”),Positron Emission Tomography (“PET”) and Computed X-ray Tomography(“CT”), by examining the same tissue using the different physicalprincipals available with each modality. CT is often used to visualizeboney structures, and blood vessels when used in conjunction with anintra-venous agent such as an iodinated contrast agent. MRI may also beperformed using a similar contrast agent, such as an intra-venousgadolinium based contrast agent which has pharmaco-kinetic propertiesthat enable visualization of tumors, and break-down of the blood brainbarrier. These multi-modality solutions can provide varying degrees ofcontrast between different tissue types, tissue function, and diseasestates. Imaging modalities can be used in isolation, or in combinationto better differentiate and diagnose disease.

In neurosurgery, for example, brain tumors are typically excised throughan open craniotomy approach guided by imaging. The data collected inthese solutions typically consists of CT scans with an associatedcontrast agent, such as iodinated contrast agent, as well as MRI scanswith an associated contrast agent, such as gadolinium contrast agent.Also, optical imaging is often used in the form of a microscope todifferentiate the boundaries of the tumor from healthy tissue, known asthe peripheral zone. Tracking of instruments relative to the patient andthe associated imaging data is also often achieved by way of externalhardware systems such as mechanical arms, or radiofrequency or opticaltracking devices.

Increasingly, functional brain simulators or brain phantoms with finedetail of functionality and structure of the brain can be created withsuch materials as cryogel. Further, combining phantoms with diffusiontracks and/or with diffusion tensor imaging (DTI) allows realisticnavigation paths and resection scenarios to be planned.

Thus, there is a desire to integrate sensors, utilize novel materialsand imaging techniques with brain phantoms to provide feedback tosurgeons regarding the successful execution of their simulated surgicalprocedures.

SUMMARY

The present disclosure discloses physiological phantoms incorporatingsensors providing a feedback metric (to the user) embedded in abiomechanical mimic of tissue of an anatomical part also known as atissue phantom. The sensors include, but are not limited to opticalfibers containing Fiber Bragg Gratings (FBG), electrical circuits, fiberoptic channels, and material substances. The sensors may be sensitive toexposures resulting from but not limited to strain, thermal changes,light, electricity, and etc. such as occurs during medical procedures inwhich a surgeon is performing a surgical intervention using a medicaldevice such as, but not limited to, a scalpel, a needle, a deep brainstimulation probe, a stimulation probe, a stimulation electrode, anoptical device, an access port used in brain or spinal surgery or anypart of the mammalian anatomy containing tissue.

The sensors may be interrogated to provide metrics related to theactions being performed on the tissue phantom. These metrics may bereflective of the success of a mock procedure being performed on thetissue phantom.

For example in a tissue phantom employing embedded fiber Bragg gratingsensors, when a strain is applied to a portion of the tissue phantom,the optical fibers will undergo strain causing a shift in the reflectionspectra from the Bragg gratings in the vicinity of the strain which isdetected by the detector, with the amount of the spectral shift beingproportional to the amount of strain experienced by the fiber at thatlocation.

The example embodiment of the anatomical (tissue) phantom as disclosedherein containing small diameter optical fibers containing strainsensitive Bragg gratings are useful in many applications. For example,the fibers may be used to emulate brain tracts in a generic brainphantom. Such generic brain phantoms may be used as general trainingaids for surgical residents and/or medical students.

They may also be used to represent brain tracts of particular importanceor relevance in a particular patient. For example, a brain phantom maybe produced for a specific patient with a neurological conditionrequiring medical intervention. In such a case a lifelike brain phantomis produced based on pre-operative imaging acquired by any one orcombination of imaging techniques. The optical fibers are thenpositioned in the parts of the brain phantom most relevant to themedical procedure (e.g., those adjacent to or along a surgical path)during the process of constructing the life-like phantom. This life-likephantom can then be used by the clinician(s) to practice the anticipatedmedical procedures for that particular patient. In an alternativeembodiment, the optical fibers are used to simulate nerve fibers anddetect applied pressure and movement in a spinal surgery phantom.

The optical fibers containing strain sensitive Bragg gratings may beused to represent specific types of oriented tissue, including but notlimited to tendons, ligaments, directional tissue and the like. Forlarger structures, in an embodiment of the tissue phantom disclosedherein enables one to detect the displacement of structures such asnatural lumens, such as for example blood vessels (veins, arteries), byaffixing the optical fibers on the outside or inside of the naturallumens. Note that the fibers may be affixed to any anatomical phantompart, such as any organ, to detect displacement of same during a medicalprocedure.

A particular advantage of the present phantoms incorporating fiber Bragggratings for strain detection is that they are optically based. Thus,phantoms constructed as disclosed herein may be used in conjunction withreal-time MRI based techniques. Particularly, for phantoms constructedto be used for emulating patient MR imaging, the high magnetic fieldswill not interfere with the optical signals, unlike electrical basedsensors, such as described by additional embodiments of the tissuephantom as disclosed herein, that may be embedded in the phantom.Specifically, brain phantoms can be produced for practicing imaging andinclude structural features that show up in MR images. In such phantomsoptical fibers may be aligned with and affixed with these structuralfeatures so that when practicing medical procedures, strain may bedetected in fibers and correlated with the MR images of thestrained/displaced optical fibers.

A further understanding of the functional and advantageous aspects ofthe invention can be realized by reference to the following detaileddescription and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments disclosed herein will be more fully understood from thefollowing detailed description thereof taken in connection with theaccompanying drawings, which form a part of this application, and inwhich:

FIG. 1 is an illustration of an example port-based surgical approach inwhich a port is inserted along the sulci to approach a tumor locateddeep in the brain.

FIG. 2 is an illustration of an example training model head and brainphantom in an exploded view, illustrating parts of the base componentand the training component.

FIG. 3 is an illustration of a brain phantom in a skull having feedbacksensors.

FIG. 4 is an illustration of a fiber optic cable in a brain phantomhaving fiber Bragg gratings.

FIG. 5 is an illustration of a brain phantom having a network offeedback sensors.

FIG. 6 (a) is a diagram showing a generic strain detection feedbacksystem.

FIG. 6 (b) is a diagram showing a generic strain detection feedbacksystems function.

FIG. 6 (c) is a diagram showing a wavelength multiplexed straindetection feedback system.

FIG. 6 (d) is a diagram showing an intensity division multiplexed straindetection feedback system.

FIG. 6 (e) is a diagram showing two OTDR based strain detection feedbacksystems.

FIG. 7 (a) is a diagram showing a time division multiplexed straindetection feedback system.

FIG. 7 (b) is a diagram showing a spatially division multiplexed straindetection feedback system.

FIG. 7 (c) is a diagram showing an electrical strain detection feedbacksystem.

FIG. 8 (a) is a diagram of a fiber Bragg grating.

FIG. 8 (b) shows the core refractive index of the fiber Bragg grating ofFIG. 8 (a).

FIG. 8 (c) shows a typical spectral response of the fiber Bragg gratingof FIG. 8 (a) showing the input light and the transmitted and reflectedlight signals.

FIG. 9 is a diagram of wavelength division multiplexing (Cooper, DavidJ. F. Time Division Multiplexing of a Serial Fibre Optic Bragg GratingSensor Array; Ottawa: National Library of Canada, 1999.

FIG. 10 is a diagram of intensity division multiplexing.

FIG. 11 is a diagram of time division multiplexing.

FIG. 12 (a) shows an OTDR signal trace.

FIG. 12 (b) shows a bending optical fiber.

FIG. 12 (c) shows an OTDRs signal trace response dependence on bendangle, Kwon, II-Bum, et al. “Multiplexed fiber optic OTDR sensors formonitoring of soil sliding” XVIII Imeko World Congress Metrology for aSustainable Development Sep. 17-22, 2006, Rio de Janeiro, Brazil. 2006;and Understanding OTDRs. Issue 1. Anritsu Corporation November 2011.

FIG. 13 (a) is a diagram of an electrical strain gauge, see Starck,Jason. “Strain Gauges.” All about Circuits Forum RSS. N.p., 2014. Web.13 Nov. 2014.

FIG. 13 (b) is a diagram of an electrical strain gauge circuit, seeStarck, Jason. “Strain Gauges.” All about Circuits Forum RSS. N.p.,2014. Web. 13 Nov. 2014.

FIG. 14 (a) is an illustration of a polarization maintaining fiber Bragggrating system; see C. M. Lawrence et al., “A Fiber Optic Sensor forTransverse Strain Measurement,” Experimental Mechanics 39 (3), 202(1999).

FIG. 14 (b) is an illustration of the angle dependent response of apolarization maintain fiber Bragg grating.

FIG. 14 (c) is an illustration of the angle dependent response of aphotonic crystal fiber Bragg grating.

FIG. 15 (a) is an illustration of a combined multiplexing systems offiber Bragg grating sensors.

FIG. 15 (b) is an illustration of a combined multiplexing systems offiber Bragg grating sensors and electrical sensors.

FIG. 16 is an illustration of a spinal phantom with intergrated feedbacksystems.

FIG. 17 is an illustration of a curving spinal phantom with intergratedfeedback systems.

FIG. 18 (i) is an illustration of a shape sensing cable.

FIG. 18 (ii) is an illustration of a shape sensing strain gauge array.

FIG. 19 is an illustration of a mock port based resection surgery on abrain phantom.

FIG. 20 is an illustration of a progressing mock port based resectionsurgery on a brain phantom.

FIG. 21 (a) depicts the sulci of the brain through a mock craniotomy andmock skull and a stimulation probe inserted through one of the sulciinto the brain phantom.

FIG. 21 (b) shows the internal structures contained within the brainphantom matrix material which replicate the tractography of the brain.

FIG. 22 is an illustration of a brain phantom with built in EM feedbacksystem for a mock deep brain stimulation (DBS) procedure.

FIG. 23 is an illustration of a brain phantom with built in opticalfeedback system for a mock DBS procedure.

FIG. 24 (a) shows the mock surgery before an access port is insertedinto a sulcus of a mock brain.

FIG. 24 (b) is an illustration of the progressing intraoperative brainphantom of FIG. 24 (a) showing the built-in feedback network for a mocktumor resection procedure and shows the internal structures containedwithin the brain phantom matrix material which replicate thetractography of the brain.

FIGS. 25 (a) and (b) are similar to FIGS. 24 (a) and (b) but shows theaccess port during cannulation to the bottom of the sulcus.

FIGS. 26 (a) and (b) are similar to FIGS. 25 (a) and (b) but depicts thesulci of the brain and the access port after it has penetrated thebottom of the sulcus as it is being advanced to the target.

FIG. 27 is an illustration of a brain phantom with an integratedfeedback system network with anatomical correlation to its detectionproperties.

DETAILED DESCRIPTION

Various embodiments and aspects of the disclosure will be described withreference to details discussed below. The following description anddrawings are illustrative of the disclosure and are not to be construedas limiting the disclosure. Numerous specific details are described toprovide a thorough understanding of various embodiments of the presentdisclosure. However, in certain instances, well-known or conventionaldetails are not described in order to provide a concise discussion ofembodiments of the present disclosure.

As used herein, the terms “comprises” and “comprising” are to beconstrued as being inclusive and open ended, and not exclusive.Specifically, when used in the specification and claims, the terms“comprises” and “comprising” and variations thereof mean the specifiedfeatures, steps or components are included. These terms are not to beinterpreted to exclude the presence of other features, steps orcomponents.

As used herein, the term “exemplary” means “serving as an example,instance, or illustration,” and should not be construed as preferred oradvantageous over other configurations disclosed herein.

As used herein, the terms “about” and “approximately” are meant to covervariations that may exist in the upper and lower limits of the ranges ofvalues, such as variations in properties, parameters, and dimensions.

As used herein, the term “patient” is not limited to human patients andmay mean any organism to be treated using the planning and navigationsystem disclosed herein.

As used herein the phrase “surgical tool” or “surgical instrument”refers to any item that may be directed to a site along a path in thepatient's body. Examples of surgical tools may include (but are notnecessarily limited to) scalpels, resecting devices, imaging probes,sampling probes, catheters, or any other device that may access a targetlocation within the patient's body (or aid another surgical tool inaccessing a location within a patient's body), whether diagnostic ortherapeutic in nature.

Since image-guided medical procedures are complex in nature and the riskassociated with use of such procedures in the brain is very high, thesurgical staff must often resort to performing a simulated rehearsal ofthe entire procedure. Unfortunately, the tools and models that arecurrently available for such simulated rehearsal and training exercisestypically fail to provide a sufficiently accurate simulation of theprocedure.

Understanding and modeling tissue deformation is important for surgeonspracticing invasive medical procedures on patients. Being able toaccurately model how various types of tissue deform will enable surgeonsto approach targets in the patient's body with minimal damage toimportant tissue. Being able to produce tissue phantoms which exhibitbiomechanical and imaging characteristics resembling those of patientsis a necessary first step in providing a viable life-like tissue phantomon which to practice medical procedures.

When performing surgical and/or diagnostic procedures that involve thebrain, neurosurgical techniques such as a craniotomy, or a minimallyinvasive procedure such as an endo-nasal surgery or a port basedsurgical method, may be performed to provide access to the brain. Insuch procedures, as indicated, the medical procedure is invasive of themammalian head. For example, in the port-based surgical methodillustrated in FIG. 1, a generally cylindrical port 100 or corridor isinserted along the sulci 110 of the brain 120 to access a tumor 130located deep in the brain 120. The cylindrical port 100 provides thesurgeon with access to the interior portion of the patient's brain beingoperated on.

According to embodiments provided herein, the simulation of suchprocedures may be achieved by providing a brain model that is suitablefor simulating the medical procedure through one or more layers of thehead. Such a procedure may involve perforating, drilling, boring,punching, piercing, stimulating, ablating, resecting, or any othersuitable methods, as necessary for an endo-nasal, port-based, ortraditional craniotomy approach. For example, some embodiments of thepresent disclosure provide brain models comprising an artificial skulllayer that is suitable for simulating the process of penetrating amammalian skull. As described in further detail below, once the skulllayer is penetrated, the medical procedure to be simulated using thetraining model may include further steps in the diagnosis and/ortreatment of various medical conditions. Such conditions may involvenormally occurring structures, aberrant or anomalous structures, and/oranatomical features underlying the skull and possibly embedded withinthe brain material.

In some example embodiments, the brain model is suitable for simulatinga medical procedure involving a brain tumor that has been selected forresection. In such an example embodiment, the brain model is comprisedof a brain material having a simulated brain tumor provided therein.This brain material simulates, mimics, or imitates at least a portion ofthe brain at which the medical procedure is directed or focused. Thesimulation of the above described medical procedure is achieved throughsimulation of both the medical procedure and the associated imagingsteps that are performed prior to surgery (pre-operative imaging) andduring surgery (intra-operative imaging). Pre-operative imagingsimulation is used to train surgical teams on co-registration of imagesobtained through more than one imaging methodology such as magneticresonance (MR), computed tomography (CT) and positron emissiontomography (PET). Appropriate co-registration geometrically alignsimages from different modalities and, hence, aids in surgical planningstep where affected regions in the human body are identified and asuitable route to access the affected region is selected.

Referring to FIG. 2, an exploded view of an example model or phantomshown generally at 250 is provided that is suitable for use in trainingor simulation of a medical procedure which is invasive of a mammalianhead. The training model 250 may be adapted or designed to simulate anyanatomical structure. It is to be understood that the person to betrained on the phantom may be selected from a wide variety of roles,including, but not limited to, a medical doctor, resident, student,researcher, equipment technician, or other practitioner, professionals,or personnel. In other embodiments, the models provided herein may beemployed in simulations involving the use of automated equipment, suchas robotic surgical and/or diagnostic systems. The present disclosurerelates to communication channels connected to sensors (such as but notlimited to strain sensors) embedded within an anatomical phantom formedfrom sections of tissue mimic. The sensors may be employed to emulatetissue which can provide information regarding local deformation of thetissue mimic forming the anatomical phantom, during mock medicalprocedures.

Types of Sensors

There are a multiplicity of sensors or sensing materials that provide afeedback metric to a user of the tissue phantom device as disclosedherein that may suffice for use in the anatomical (tissue) phantoms asdisclosed above. Examples of such sensors or sensing materials includebut are not limited to Fiber Bragg Gratings (FBGs), electrical straingauges, organic semiconductor strain gauges, photo-reactive substances(materials), thermally-reactive substances (materials), electrochromicsubstances (materials), radiochromic substances (materials), fiber opticchannels, polarization maintaining optic fibers, photonic crystalfibers, EM receivers, and etc. The type of strain sensors employed maydepend on varying factors such as the communication channel used, theanatomy of the phantom, properties of the tissue phantom material(s),The accuracy level of the sensors, the cost of the sensors, theinteraction of the type of sensor with the tissue phantom, the externalenvironment in which the tissue phantom device will be utilized and etc.

In addition each sensor or sensing material type may typically have itsown preferred communication channel where applicable for example FiberBragg Grating sensors need to be used in combination with optical fiberswhile electrical sensors may be connected through electrical wires, andorganic strain gauges may be connected through a printed flexiblecircuit or have wireless communication channels, in addition an electrochromic substance (material) may not even require a communicationchannel. It should be noted before continuing that fiber Bragg gratingswill be referred to as FBGs henceforth.

An embodiment of the device disclosed herein is shown in FIG. 3 to 5wherein FBG sensors 14 are connected by fiber optic communicationchannels 12 and are embedded in a brain phantom. The bottom frame inFIG. 3 and FIGS. 4 and 5 depict the inside of the phantom 16, toillustrate this FIG. 3 has dashed lines where the surface is beingsuperimposed on an internal view of the phantom and FIGS. 4 and 5 haveno surface texture 9. In general, the device will include the brainphantom 16 shown in FIG. 3 containing a number of optical fibers 12constructed with a known number of FBGs 14 at known distances along thelength of the fibers 12. The known number and distance of the FBGs 14may be used to locate the source of a detected strain as will bedescribed in further detail below. While typical FBGs suffice for use inmost phantoms, in some embodiments small diameter (40-50 microns)optical fibers containing Bragg gratings embedded in tissue phantommaterial(s) sufficiently small in diameter may be beneficial so as tonot induce weakness in the tissue phantom material(s). Nevertheless, theproperties of the tissue phantom material(s) can be tailored tocompensate for any weakness induced by the presence of the opticalfibers 12.

For example, if the tissue phantom is a brain, a useful material isthermally cycled polyvinyl alcohol (PVA) in which the biomechanicalproperties may be tuned depending on the number of thermal cycles thematerial is subject to during production of the tissue mimic.Optionally, in an embodiment such as shown in FIG. 5 small diameteroptical fibers 15 can represent directional brain tracts which connectvarious parts of the brain 16, such fibers being of the order of 40microns in diameter. The fibers may be produced with different Bragggratings with the different Bragg gratings being employed to designatethe different directions of brain tracts, for example brain tracts goingfront to back (such as the optic tract) in a person's brain 16 may bedesignated using one type of Bragg grating, brain tracts going from topto bottom 15 in a person's brain may be designated using another type ofBragg grating etc. Alternatively, different Bragg gratings may be usedto designate brain tracts on the basis of functionality, notdirectionality, such as the optic tract 12.

Referring to FIG. 4, there is shown an exemplary strain detectionfeedback system applied and incorporated as part of a tissue phantom. Atissue phantom may be constructed to emulate any part of a patient'sbody, animal in general and human in particular. The sensors of thestrain detection feedback system in this embodiment are Fiber BraggGratings (FBG) comprised of Bragg gratings 14 formed as part of smalldiameter optical fibers 12. These sensors may be embedded in a tissuephantom material 16 selected to mimic an anatomical part of the patientas shown in FIG. 4. The material of tissue phantom 16 may contain adirectional tissue component 18 which may be selected to mimic any oneor combination of muscle tissue, ligaments, tendons, white matter brainfiber tracts, nerve bundles, spinal tissue, any natural lumens such asblood vessels and the like. This directional tissue component 12 may beformed of the optical fiber(s) of the strain detection feedback systemto simultaneously provide a more accurate biomechanical model as well asfeedback for the user, such as a measure of strain along the length ofthe fibers.

The strain detection feedback system employed in this embodiment isformed of the optical fiber 12 containing the FBG sensors connected to alight source 22, and a detector 24, at the same or alternate ends of theoptical fiber 12, for detecting the reflected or transmitted lightspectrum of the FBG and inferring a stress dispersion arising from astrain at a FBG embedded in the tissue phantom 16 as described infurther detail below.

The basic principle of operation normally used in a FBG based sensorsystem is to monitor the shift in wavelength of the reflected lightrelative to the Bragg wavelength. The Bragg wavelength λ_(B) is obtainedusingλ_(B)=2n

  (1)

where

is the grating period and n is the effective index of the fiber core.The Bragg wavelength shifts through a change of the core effective indexand the grating pitch representing varying levels of temperature andstrain. The Bragg wavelength shift in response to applied strain ε isobtained using:∂λ/∂ε=λ_(B)(1−p _(e))  (2)

where p_(e) is the effective photo-elastic coefficient. Given the Braggwavelength λ_(B)=1550 nm and p_(e)=0.22 for fused silica, the strainsensitivity is calculated at 1.21 pm/με. A diagram of this phenomena isprovided in FIG. 8 and described further below.

Using a system of detectors, light sources, and FBGs connected to one ormore fibers there exist many interrogation techniques for determiningthe magnitude and location of strain being imposed on the fiber(s).

In some embodiments, the fiber optic containing the FBG sensors embeddedin the tissue phantom material may be deliberately aligned duringproduction of the phantom, to mimic directional tissue components, suchas direction muscle tissue, ligaments, tendons, brain tracts etc. Thisallows for measurement of actual deformation and/or strain at selectedlocations, and along selected directions, in the tissue phantom asdisclosed herein during practice procedures and this may be compared todeformation predicted by tissue deformation models of the phantom aswell.

Optical fibers could be threaded though the soft mold in which the brainphantom is produced and supported at specific locations via pins whenthe phantom is being produced.

Types of Strain Detectors

Variations of the embodiment described above and depicted in FIG. 5 maybe implemented using a multiplicity of strain detectors and detectionmechanisms as is depicted in FIGS. 6 and 7, by substituting these straindetection feedback systems for the strain detection feedback systemshown in FIG. 4 and described above. These figures show block diagramsof strain detection feedback systems that may be implemented in thetissue phantom device as disclosed herein to allow the detection ofstrain at various locations on or in the anatomical phantom. The varioustypes of detection feedback systems will be described as follows. Itshould be noted that any single implementation of a detection feedbacksystem or combination of detection feedback systems thereof may beimplemented for use as part of the device disclosed herein. Althoughmost of the detection feedback systems being described are well known inthe art these are not to limit the implementations whereby uniquesystems may arise.

Generic Block Diagram

The first block diagram FIG. 6 (a) shows a generic strain detectionfeedback system that may be implemented in an embodiment of the devicedisclosed herein such as that depicted in FIG. 3 to 5 and describedabove. It follows then that the communication channel 602, strainsensors 604, and detector/source 600 of a generic strain detectionfeedback system are embodied as a fiber optic communication channel 12,FBGs 14, and an optical detector/optical source 24 respectively in theembodiment shown in FIG. 3 to 5. The light source 22 in the embodimentdepicted in FIG. 3 to 5 is a source used to generate an energy signalrequired to allow the sensors to function. In general a strain detectionfeedback system may or may not require an energy source depending on thetype of sensors chosen.

The diagram FIG. 6 (b) depicts the functioning of a generic straindetection feedback system. In such systems a signal is generally sentfrom the sensors to the detector to be analyzed against a reference. Anexample of this system is shown in the section 609 of the diagram FIG. 6(b). In the diagram the sensors 604 send signals 605 to the detector600. The detector than analyzes the signal 605 and determines the strainon the particular sensors. In many embodiments these signals may be sentalong the same communication channel such as 602 or may be sent alongseparated channels, such as channels 708 a and 708 b shown in FIG. 7 (b)or equivalently multiple separate wireless communication channels, orany combination thereof.

Commonly most strain detection feedback systems function by sending anenergy signal from a source 600 which is returned to a detector afterbeing altered (including reflecting the signal) in some way by a sensor604. The return signal is then analyzed in comparison to the initiallysent signal or some reference to determine the amount of strain on aparticular sensor. An example of this is shown at the top section 607 ofFIG. 6 (b). In this example the sent signals 603 are being altered bythe sensors 604 depending on the strain applied to them and sent back asreturn signals 605 to the detector 600 along the communication channel602. It follows then that the communication channel 602, strain sensors604, detector 600, signal 603, and return signal 605 of a generic straindetection feedback system are embodied as a fiber optic communicationchannel 12, FBGs 14, an optical detector 24, and reflected opticalreturn signal 20 respectively in the embodiment shown in FIG. 4.

The light source 22 employed in the embodiment depicted in FIG. 4 mayemit an optical signal 22 of variable bandwidth and wavelength 18 whichis partially or fully reflected, at the Bragg wavelength, in the form ofan optical return signal 20 by FBGs 14 to the optical detector 24 wherethe signal is then analyzed to determine the amount of strain applied tothe specific strain sensor. It should be noted that any light source anddetector required in the embodiments of the tissue phantom as disclosedherein may be in the form of a broadband, tunable band, or tunablewavelength source or detector and maybe used in any combination thereofto meet the requirements of the strain detection feedback system as isknown in the art.

It is noted that there may be several sources of strain being indicatedby the sensors during the mock surgical procedure for several reasons.The main one is by the clinician physically contacting the sensorsection or fiber and causing strain by the surgical tool in contact withthe sensors. It may also arise due to phantom material in closeproximity to the sensor being displaced by the surgical tool intocontact with the sensor.

The generic apparatus and generic principle function of strain detectionfeedback systems as shown in FIG. 6 (a) and FIG. 6 (b) have specificimplementations reliant on the choice of hardware employed by the straindetection feedback system. However in order for a strain detectionfeedback system to uniquely locate its strain sensors positions andtheir respective strain magnitudes, the hardware typically is designedfor integration with a complementary interrogation technique. There aremany combinations of interrogation techniques and hardware which may beused to form a multitude of strain detection feedback systems which arewell known to those skilled in the art.

Some examples of strain detection feedback systems that may be employedin the tissue phantom disclosed herein are described in detail asfollows. It should be noted that any strain detection feedback system asdescribed may be implemented as part of the device disclosed herein toform a phantom integrated with a strain detection feedback system. Inparticular embodiments any of the strain detection feedback systemsdescribed as follows may be integrated into a phantom such as shown inFIGS. 3 and 16. In addition the strain detection feedback systems whichwill be described are provided as examples of the embodiments of thetissue phantom device as disclosed herein employing strain detectionfeedback systems only and are not to be interpreted as limitingembodiments of the tissue phantom device as disclosed herein. It shouldalso be noted that the detection of strain need not be limited toproviding a magnitude of strain and may be construed as any indicationthat a strain is being applied on the tissue phantom device as disclosedherein.

Wavelength Division Multiplexing Using Fiber Bragg Gratings

The first strain detection feedback system to be described will be awavelength division multiplexed system employing FBG strain sensors anexample of which is disclosed in the book [Cooper, David J. F. TimeDivision Multiplexing of a Serial Fibre Optic Bragg Grating SensorArray; Ottawa: National Library of Canada, 1999. This system may beconsidered as a further refinement of the embodiment described above inthat it has the additional attribute of an interrogation technique. Ablock diagram of this embodiment is provided in FIG. 6 (c).

The principle function of this first strain detection feedback systemwill be reiterated as follows for clarity with reference to FIG. 8[Wikipedia contributors. “Fiber Bragg grating.” Wikipedia, The FreeEncyclopedia. Wikipedia, The Free Encyclopedia, 31 Aug. 2014. Web. 14Nov. 2014.]. This strain detection feedback system embodiment functionsby having FBGs 612, formed into a fiber optic channel 610, reflectincoming optical signals 820 (FIG. 8) at a Bragg wavelength back alongthe channel to the detector 608, while the remaining signal 830 (FIG. 8)is transmitted and continues along the fiber optic channel 610. As theFBGs in this embodiment are placed under strain their Bragg wavelength(λ_(B)) shifts 850 according to the following equationΔλ_(B)=λ_(BO)(1−P _(e))ε+λ_(BO)(α

−α_(η))ΔTλ_(BS)−λ_(BO)=λ_(BO)(1−P _(e))ε+λ_(BO)(α

−α_(η))ΔTλ_(BS)=λ_(BO)(1−P _(e))ε+λ_(BO)(α

−α_(η))ΔT+λ _(BO)

Where α and α_(n) are the thermal expansion coefficient of the opticalfiber and the thermo optic-coefficient respectively, λ_(BO) (i.e.λ_(B)=λ_(BO)) is the Bragg wavelength of the FBG under no strain, andλ_(BS) (i.e. λ_(B)=λ_(BS)) is the Bragg wavelength of the FBG under aparticular strain. Therefore the wavelength of the reflected signal 860(λ_(BS)) from the FBG 612 may be compared to the Bragg wavelength of theFBG under no strain λ_(BO) to determine the strain (ε) on the sensor 612(FIG. 8), given the temperature change is accounted for or held constantthroughout.

In this embodiment shown in FIG. 6 (c) the generic communication channel602, strain sensors 604, and detector 600 of the generic straindetection feedback system are embodied as a fiber optic communicationchannel 610, FBGs 612, and an optical detector/illumination source 608respectively.

This embodiment functions in a similar manner to the generic functioningof a strain detection feedback system depicted in FIG. 6 (b). Where thesent signals 603 are being altered by the sensors 604 and sent back asreturn signals 605 to the detector 600 along the communication channel602. It follows then that the communication channel 602, strain sensors604, detector 600, signal 603, and return signal 605 of a generic straindetection feedback system are embodied as a fiber optic channel 610, FBGstrain sensors 612, optical detector 608, optical input signal 820, andreflected input signals 860 respectively in the system in FIG. 6 (c).

To ease explanation of the embodiment being described herein henceforththe term “reflection band” will refer to the range of all possible Braggwavelengths an FBG may reflect incoming light at back to the detector608, under the influence of any applied strain ranging from no appliedstrain (λ_(BO)) to the maximum strain. Where the maximum strain maycorrespond to the level of strain which would cause the FBG to fracture,the level of strain at the maximum bending amount of the FBG, or anarbitrary predetermined imposed strain limit. In addition the term“original Bragg wavelength” will be used to refer to the Braggwavelength of an FBG under no strain and the term “altered Braggwavelength” will be used to refer to the Bragg wavelength of an FBGunder an arbitrary level of applied strain.

The interrogation technique of wavelength division multiplexing isapplied in this embodiment as shown in FIG. 6 (c) in order todifferentiate which sensor 612 (i.e. FBG: 1 . . . FBG: 6) a reflectedinput signal (return signal) 860 is derived from and determine themagnitude of strain being applied at that specific FBG sensor 612. Inorder to apply this technique the multiple FBG strain sensors 612labelled FBG: 1 . . . FBG: 6, must be located at various known locationsalong the length of the fiber optic cable 610 and must have particularreflection bands. This technique works by segmenting the emissionspectrum of the source into intervals (reflection bands) wherein eachinterval corresponds to a specific sensor. The segmentation is achievedby employing FBGs (FBG: 1 . . . FBG: 6) with original Bragg wavelengths(λ_(BO-1) . . . λ_(BO-6)) such that the reflection band of that FBGsensor will not overlap with any other FBG sensors reflection band.

An example of this segmentation is depicted in FIG. 9 [Cooper, David J.F.; Time Division Multiplexing of a Serial Fibre Optic Bragg GratingSensor Array; Ottawa: National Library of Canada, 1999. In the figurethere are N reflection bands 930 each one corresponding to a particularFBG sensor 612 with a particular reflection band 930. The intervalsdepicted by the reflection bands 930 show the range of wavelengths atwhich an input signal may be reflected and returned to the detector bythe FBG. The wavelength of the reflected input signal will be thealtered Bragg wavelength 860 of the FBG sensor. The detector 608 maythen analyze the reflected input signal to determine its wavelength (orrange of wavelengths). Following this determination the wavelength maybe used to assign the reflected input signal to a specific FBG sensor(FBG: 1 . . . FBG: 6) depending on which reflection band 930 (0 . . . 6)the wavelength of the reflected input signal falls within. Once assigneda specific FBG sensor the following equation may be used to determine astrain value corresponding to the reflected input signal.

$ɛ = {\frac{\lambda_{BS} - \lambda_{BO}}{\lambda_{BO}\left( {1 - P_{e}} \right)} - \frac{\left( {\alpha_{\Lambda} - \alpha_{\eta}} \right)\Delta\; T}{\left( {1 - P_{e}} \right)}}$

Where λ_(BO) is the original Bragg wavelength of the assigned FBGsensor, λ_(BS) is the wavelength of the reflected input signal and ΔT isthe change in temperature at the FBG. The assigned FBG sensor along withthis calculation then provides information as per the amount of appliedstrain and the location of that applied strain (i.e. a specific sensor612 (FBG: 1 . . . FBG: 6)) along the fiber optic channel containing theFBGs.

Intensity Division Multiplexing Using Fiber Bragg Gratings

The second strain detection feedback system to be described will be anIntensity division multiplexed system employing FBG strain sensors anexample of which is disclosed in U.S. Pat. No. 6,879,742 entitled UsingIntensity And Wavelength Division Multiplexing For Fiber Bragg GratingSensor System. This system is similar to the embodiment described abovein that it segments a detectable range (in this case the intensity ofthe reflected input signal) in order to determine which FBG sensor thereflected input signal was derived from. An exemplary block diagram ofthis embodiment is provided in FIG. 6 (d). It should be noted that theemployed embodiment utilizes FBG sensors (FBG: 1 a . . . FBG: 1 c)having the same original Bragg wavelengths (λ_(BO1)) but differing inluminous reflectivity (i.e. percentage of signal at wavelength (λ_(BO1))which is reflected).

The principle function of this second strain detection feedback systemis identical to that of the first system above where the altered Braggwavelength (λ_(BS)) is defined by the following equationλ_(BS)=λ_(BO)(1−P _(e))ε+)λ_(BO)(α

−α_(η))ΔT+λ _(BO)

Therefore the wavelength of the reflected signal 860 (λ_(BS)) from theFBG may be compared to the Bragg wavelength of the FBG under no strainλ_(BO) to determine the strain (ε) on the sensor 618, given thetemperature change is accounted for or held constant throughout.

In this embodiment shown in FIG. 6 (d) the generic communication channel602, strain sensors 604, and detector 600 of the generic straindetection feedback system are embodied as a fiber optic communicationchannel 616, FBGs 618, and an optical detector/illumination source 614respectively.

This embodiment functions in a similar manner to the generic functioningof a strain detection feedback system depicted in FIG. 6 (b). Where thesent signals 603 are being altered by the sensors 604 and sent back asreturn signals 605 to the detector 600 along the communication channel602. It follows then that the communication channel 602, strain sensors604, detector 600, signal 603, and return signal 605 of a generic straindetection feedback system are embodied as a fiber optic channel 614, FBGstrain sensors 616, optical detector 618, optical input signal 820 (FIG.8), and reflected input signals 1000, 1010, and 1020 shown in FIG. 10respectively in the strain detection feedback system block diagram shownin FIG. 6 (d).

To ease explanation of the embodiment being described herein henceforththe term “intensity band” will refer to the range of all possibleluminous intensities (within a tolerance or not) an FBG may reflectincoming light at, back to the detector 608. This “intensity band” willlikely be centered on the reflectivity value of the particular FBGwherein the likelihood of an input signal being reflected at aparticular luminous intensity may be normally distributed around thisreflectivity value as the mean.

The interrogation technique of intensity division multiplexing isapplied in the embodiment being described herein as shown in FIG. 6 (d)in order to differentiate which sensor 618 (i.e. FBG: 1 a . . . FBG: 1c) a reflected input signal (return signal) 1000, 1010, or 1020 isderived from and determine the magnitude of strain being applied at thatspecific sensor 618. In order to apply this technique the multiple FBGstrain sensors 618 labelled FBG: 1 a . . . FBG: 1 c, must be located atvarious known locations along the length of the fiber optic cable 610and must have specific intensity bands. This technique works bysegmenting the intensity detection range into intervals wherein eachinterval corresponds to a specific sensor. The segmentation is achievedby employing FBGs (FBG: 1 a . . . FBG: 1 c) with different reflectivityvalues.

An example of this segmentation is depicted in FIG. 10. In the figurethere are 3 intensity bands between the band limits 1030, 1040, 1050,and 1060, each one corresponding to a particular FBG sensor 618 (FBG: 1a, FBG: 1 b, and FBG: 1 c) with specific intensity bands (intensity band#1, intensity band #2, and intensity band #3 respectively). Theintervals depicted by the intensity bands show the range of intensitiesat which an input signal may be reflected and returned to the detectorby a specific FBG. The wavelength of the reflected input signal will bethe altered Bragg wavelength 860 of the FBG sensor. The detector 614 maythen analyze this reflected input signal to determine its wavelength (orrange of wavelengths). Following this determination the intensity rangemay be used to assign the reflected input signal to a specific FBGsensor (FBG: 1 a . . . FBG: 1 c) depending on which intensity band thewavelength of the reflected input signal falls within. Once assigned aspecific FBG sensor the following equation may be used to determine astrain value corresponding to the reflected input signal.

$ɛ = {\frac{\lambda_{BS} - \lambda_{BO}}{\lambda_{BO}\left( {1 - P_{e}} \right)} - \frac{\left( {\alpha_{\Lambda} - \alpha_{\eta}} \right)\Delta\; T}{\left( {1 - P_{e}} \right)}}$

Where λ_(BO) is the original Bragg wavelength of the assigned FBGsensor, λ_(BS) is the wavelength of the reflected input signal and ΔT isthe change in temperature at the FBG. The assigned FBG sensor along withthis calculation then provides information as per the magnitude ofapplied strain and the location of that applied strain (i.e. a specificsensor 618).

Time Division Multiplexing Using Fiber Bragg Gratings

The fourth strain detection feedback system to be described will be atime division multiplexed system employing FBG strain sensors. Thissystem is similar to the embodiments described above in that it segmentsa detectable range (in this case the time of arrival of the reflectedinput signal) in order to determine which FBG sensor the reflected inputsignal was derived from. An exemplary block diagram of this embodimentis provided in FIG. 7 (a). It should be noted that the employedembodiment utilizes FBG sensors (FBG: 1, FBG: 1′, FBG: 1″) having thesame original Bragg wavelengths (λ_(BO1)) and the same reflectivity's(i.e. percentage of signal at wavelength (λ_(BO1)) which is reflected).The reflectivity of the FBGs in this case must be divided amongst theFBGs such that the percentages accumulate to a maximum of 100% so thatthe luminous intensity is enough such that it reaches the last sensorwith enough luminous intensity to produce a return signal detectable bythe detector 700.

The principle function of this fourth strain detection feedback systemis identical to that of the first system above where the altered Braggwavelength (λ_(BS)) is defined by the following equationλ_(BS)=λ_(BO)(1−P _(e))ε+)λ_(BO)(α

−α_(η))ΔT+λ _(BO)

Therefore the wavelength of the reflected signal 860 (λ_(BS)) from theFBG may be compared to the Bragg wavelength of the FBG under no strainλ_(BO) to determine the strain (ε) on the sensor 704, given thetemperature change is accounted for or held constant throughout.

In this embodiment shown in FIG. 7 (a) the generic communication channel602, strain sensors 604, and detector 600 of the generic straindetection feedback system shown in FIG. 6 (a) are embodied as a fiberoptic communication channel 702, FBGs 704, and an optical detector 700and illumination source 710 respectively.

This embodiment functions in a similar manner to the generic functioningof a strain detection feedback system depicted in FIG. 6 (b). Where thesent signals 603 are being altered by the sensors 604 and sent back asreturn signals 605 to the detector 600 along the communication channel602. It follows then that the communication channel 602, strain sensors604, detector 600, signal 603, and return signal 605 of a generic straindetection feedback system are embodied as a fiber optic channel 702, FBGstrain sensors 704, optical detector 700, optical input signal 820, andreflected input signals respectively in the system shown in FIG. 7 (a).

To ease explanation of the embodiment being described herein henceforththe term “time range” will refer to the interval of time in which allpossible reflected input signals by a particular FBG 704 may return tothe detector 700 (with or without an error tolerance). This “time range”may be centered on the mean time it would take the initial signal 1100to return to the detector after emission by the source 710 with upperand lower limits defined by a confidence interval. Wherein it is knownto a predetermined confidence, such as a 95%, that the time it takesfrom initial emission for a signal to be reflected by a specific sensorand return to the detector is in the time interval bounded by theselimits. Some exemplary time ranges are shown in FIG. 11.

The interrogation technique of time division multiplexing may be appliedin the tissue phantom embodiment as described herein and shown in FIG. 7(a) in order to differentiate which FBG sensor 704 (i.e. FBG: 1, FBG:1′, and FBG: 1″) a reflected input signal (return signal) (1110, 1120,and 1130) is derived from and determine the magnitude of strain beingapplied at that specific sensor 704. In order to apply this techniquethe multiple FBG strain sensors 704 labelled FBG: 1, FBG: 1′, and FBG:1″, must be located at various known locations along the length of thefiber optic cable 702 and must have specific time ranges. This techniqueworks by segmenting the temporal detection range into intervals whereineach interval corresponds to a specific sensor. The segmentation isachieved by placing the FBGs along the fiber optic channel 702 atspecific distances such that the time of flight measurements (amount oftime it takes for a signal to travel from the source to the specific FBGand travel back) detectably differ. An example of this segmentation isdepicted in FIG. 11. In the figure there are 3 time ranges 1140, 1150,and 1160 each one corresponding to a particular FBG sensor 704 (FBG: 1,FBG: 1′, and FBG: 1″). The intervals depicted by the time ranges showthe intervals of time after initial emission of a signal 1100 at which areflected input signal may return to the detector after being reflectedby a specific FBG 704. The wavelength of this reflected input signalwill be the altered Bragg wavelength of the FBG sensor. The detector 700may then analyze this reflected input signal to determine its wavelength(or range of wavelengths). Following this determination the timeinterval may be used to assign the reflected input signal to a specificFBG sensor (FBG: 1, FBG: 1′, or FBG: 1″) depending on which time rangethe reflected input signal returns within. Once assigned a specific FBGsensor the following equation may be used to determine a strain valuecorresponding to the reflected input signal.

$ɛ = {\frac{\lambda_{BS} - \lambda_{BO}}{\lambda_{BO}\left( {1 - P_{e}} \right)} - \frac{\left( {\alpha_{\Lambda} - \alpha_{\eta}} \right)\Delta\; T}{\left( {1 - P_{e}} \right)}}$

Where λ_(BO) is the original Bragg wavelength of the assigned FBGsensor, λ_(BS) is the wavelength of the reflected input signal and ΔT isthe change in temperature at the FBG. The assigned FBG sensor along withthis calculation then provides information as per the amount of appliedstrain and the location of that applied strain (i.e. a specific sensor704 (FIG. 7 (a))) along the fiber optic channel.

Spatial Division Multiplexing Using Fiber Bragg Gratings

The fourth strain detection feedback system to be described will be aspatial division multiplexed system employing FBG strain sensors. Anexemplary block diagram of this embodiment is provided in FIG. 7 (b). Itshould be noted that the employed embodiment utilizes FBG sensors havingthe same original Bragg wavelengths (λ_(BO1)) and the samereflectivity's (i.e. percentage of signal at wavelength (λ_(BO1)) whichis reflected). In this embodiment however there are two communicationchannels used to differentiate between the FBG sensors.

The principle function of this fourth strain detection feedback systemis identical to that of the first system above where the altered Braggwavelength (λ_(BS)) is defined by the following equationλ_(BS)=λ_(BO)(1−P _(e))ε+λ_(BO)(α

−α_(η))ΔT+λ _(BO)

Therefore the wavelength of the reflected signal 860 (λ_(BS)) (FIG. 8)from the FBG 800 may be compared to the Bragg wavelength of the FBGunder no strain λ_(BO) to determine the strain (ε) on the sensor 727(FIG. 7 (b)), given the temperature change is accounted for or heldconstant throughout. In this embodiment shown in FIG. 7 (a) the genericcommunication channel 602, strain sensors 604, and detector 600 of thegeneric strain detection feedback system shown in FIG. 6 (a) areembodied as two fiber optic communication channels 723 and 725, FBGs727, and an optical detector/illumination source 721 respectively.

This embodiment functions in a similar manner to the generic functioningof a strain detection feedback system depicted in FIG. 6 (b). Where thesent signals 603 are being altered by the sensors 604 and sent back asreturn signals 605 to the detector 600 along the communication channel602. It follows then that the communication channel 602, strain sensors604, detector 600, signal 603, and return signal 605 of a generic straindetection feedback system are embodied as a fiber optic channels 725 and727, FBG strain sensors 727, optical detector 721, a generic opticalinput signal, and a generic reflected input signal respectively in thesystem shown in FIG. 7 (b).

The interrogation technique of spatial division multiplexing is appliedin the embodiment being described herein as shown in FIG. 7 (b) in orderto differentiate which FBG sensor 727 a reflected input signal (returnsignal) is derived from and determine the magnitude of strain beingapplied at that specific sensor 727. In order to apply this techniquethe two FBG strain sensors 727 labelled FBG: 3, must be located atvarious known locations along the length of separate fiber opticchannels 723 and 727.

In order to apply this technique (i.e. excluding other multiplexingtechniques) with N FBG sensors the system would need to employ n=N fiberoptic channels. This technique works by identifying which fiber opticchannel the reflected input signal is coming from and once known thespecific FBG that corresponds to that channel. Determining which fiberoptic channel the signal is coming from may be achieved by employing aseparate source and detector for each fiber optic channel and connectingthe detectors output to a microcontroller programmed to differentiatebetween the inputs and calculate the strain based on the signals asfollows. It should be noted that many optical detectors such as the onesdescribed above are designed using microcontrollers and thus themicrocontroller mentioned herein may be superfluous to the separatedetectors and the two may be interfaced without an externalmicrocontroller. The wavelength of this reflected input signal will bethe altered Bragg wavelength of the FBG sensor. The detector 721 maythen analyze this reflected input signal to determine its wavelength (orrange of wavelengths). Following this determination the fiber opticchannel of the reflected input signal may be used to assign thereflected input signal to a specific FBG sensor depending on which fiberoptic channel the reflected input signal was received from. Onceassigned a specific FBG sensor, the following equation may be used todetermine a strain value corresponding to the reflected input signal.

$ɛ = {\frac{\lambda_{BS} - \lambda_{BO}}{\lambda_{BO}\left( {1 - P_{e}} \right)} - \frac{\left( {\alpha_{\Lambda} - \alpha_{\eta}} \right)\Delta\; T}{\left( {1 - P_{e}} \right)}}$

Where λ_(BO) is the original Bragg wavelength of the assigned FBGsensor, λ_(BS) is the wavelength of the reflected input signal and ΔT isthe change in temperature at the FBG. The assigned FBG sensor along withthis calculation then provides information as per the amount of appliedstrain and the location of that applied strain (i.e. a specific sensor727).

Optical Time Domain Reflectometry in Fiber Optic Channels

In addition to FBG based strain detection feedback systems there existsother forms of optical strain detection feedback systems that may beused to detect strain or faults within a fiber optic channel. A commonexample of such a system is an Optical Time Domain Reflectometry systemwhich will be referred to as OTDR henceforth. Two exemplary OTDR systemset ups are shown in FIG. 6 (e). The basic set up of such a system is tohave a signal source 628 and detector 620 attached to the fiber opticchannel (622 or 626) to be monitored.

The bottom channel 626 shown in the figure represents a basic OTDRsystem. Such a system is described in the report [Understanding OTDRs.Issue 1. Anritsu Corporation November 2011]. An OTDR system functions byinjecting a fiber optic channel with an optical signal pulse andmeasuring the optical signal which is reflected back to the point ofinjection at discreet time points until the injected signal reaches theend of the channel. Using time of flight calculations and knowing thespeed of light in the channel the return signals are then correlated toa specific distance along the channel where they originated essentiallycreating a signal trace of distance along channel vs. signal.

An example of such a signal trace is provided in FIG. 12 (a). In generalthe injected signal is reflected back to the detector as a result of twotypes of phenomena the first being Rayleigh backscattering and thesecond being Fresnel reflection. Rayleigh backscattering results fromthe injected signal interacting with impurities (also termed dopants) inthe fiber optic cable and scattering in all directions, wherein thesignal picked up by the detector is the portion of the scattered signalwhich was oriented back towards detector. Rayleigh backscattering occursconsistently along the length of the fiber optic cable, additionally themagnitude of interaction is more or less proportional to the strength ofthe signal at the point (distance along the fiber optic cable) ofinteraction. With no other phenomenon affecting the injected signal thesignal trace should resemble a downward sloping line proportional to theloss in injected signal strength as a result of the continuous Rayleighbackscattering interactions along the length of the fiber optic cable.

An example of an OTDR signal trace is shown in FIG. 12 (a). It isapparent from the figure that the segments 1200 labelled BackscatterLevel show characteristic properties of Rayleigh backscattering.Alternatively Fresnel reflection occurs at any points in the fiber opticchannel where the injected signal is transmitted from a region of onedensity to a region with a different density. Fresnel reflection mayoccur at specific points along the fiber optic cable where such adensity shift may occur such as at a splice point, a damaged fiber area,or the end of the fiber optic channel. When the phenomenon occurs on thetrace the intensity of the signal which is reflected back is generallymuch greater than the consistent Rayleigh backscattering occurring inthe background. Therefore in the event of a Fresnel Reflection it iscommon to see a spike on the OTDR trace. Examples of such a spikes areshown as 1204 in the FIG. 12 (a). As is apparent from the figure thesignal at beginning and ending of the fiber shown on the left and rightsides of the cursors 1202 and 1206 respectively both produce a Fresnelreflection event indicative of the change in density of the medium.Another event that may occur is a sudden loss of signal termed a “pointloss” 1208 and characterized by a dip in the Rayleigh backscatter level1200. Such an event may be indicative of a fusion splice or a stresspoint in the fiber optic channel where light is escaping.

In order to employ a basic OTDR system in the tissue phantom device asdisclosed herein a comparison of an initial signal trace against asignal trace taken after a mock operation is performed on the tissuephantom may be acquired. By subtracting the two traces by using acomputer for example any differences will be revealed and may beanalyzed to infer if any significant changes to the fiber optic channelsuch as the ones described above may have potentially occurred. Inaddition, the magnitude of strain or other force that may have causedsuch a change may also be determinable given the relative difference ofsignals at distances along the comparison signal trace.

An alternative strain detection feedback system which employs an OTDRdetector and sensor interprets the bend loss in optical fibers todetermine the bending angle or equivalent, of the fiber from its initialposition. Such a system is depicted in FIG. 6 (e) along the fiber opticchannel 610. This system employs a built-in displacement sensor to moreaccurately measure the strain at specific sensor locations along thelength of the channel. To do so the system uses pairs of fiber opticchannel integrated mirrors to provide a relative change in the signalstrength over an interval of fiber optic channel. The relative changemay then be compared to a known table to quantify the amount of bendingthe channel incurs between the mirrors.

An example of this system is provided in the paper [Kwon, II-Bum, et al.“Multiplexed fiber optic OTDR sensors for monitoring of soil sliding.”XVIII Imeko World Congress Metrology for a Sustainable Development Sep.17-22, 2006, Rio de Janeiro, Brazil. 2006]. The principle function ofthis strain detection feedback system will be further elaborated withreference to FIG. 6 (e) along the fiber optic channel 610, FIG. 12 (b),and FIG. 12 (c). Each OTDR sensor 624 shown in FIG. 6 (e) is formed oftwo fiber optic channel integrated mirrors designed to reflect apercentage of the luminous intensity of an input signal injected at oneend of the fiber back to the point of injection. The mirror closest tothe source 628 that injects the signal is termed the reference mirrorand will provide the reference signal and the mirror further from thesource will be termed the sensor mirror and will provide the sensingsignal. Both mirrors are designed to reflect the same luminousintensity. The mirrors are oriented around an interval of fiber opticchannel that will define the region where the acquired bending angle orequivalent information of the sensor will refer to. FIGS. 12 (b) and (c)show the dependence of the bending angle of the interval on the relativevalue of the reflected signals by both the reference and sensing mirrorsaccording to the equation provided as follows.

${{Normalized}\mspace{14mu}{OTDR}\mspace{14mu}{Signal}} = {C\left\{ {\left( \frac{V_{r} - V_{s}}{V_{r}} \right)_{i} - \left( \frac{V_{r} - V_{s}}{V_{r}} \right)_{o}} \right\}}$

Where C is a proportionality constant

$\left( \frac{V_{r} - V_{s}}{V_{r}} \right)_{i}$is the normalized ratio at some time i after the starting ratio

$\left( \frac{V_{r} - V_{s}}{V_{r}} \right)_{o}$is taken at time o. The values depicted with V_(r) and V_(s) are theinduced detector outputs in arbitrary units by the reflected signals atthe detector 620 by the reference and sensor mirrors respectively of thesensor 624. The normalized ratios are used to offset the naturalreduction in signal at successive distances along the optical fiberchannel resulting from Rayleigh Backscattering and other sources ofsignal loss. The plot shown in FIG. 12 (c) shows the dependence of theNormalized OTDR Signal, as calculated above, on the rotation angle 1212of the interval of fiber optic channel contained within the sensor 624.This strain detection feedback system may be employed in an embodimentof the tissue phantom device disclosed herein wherein the bending of thefiber optic channels would be indicative of the amount of strain thatthose fibers may have been exposed to.

In this embodiment shown in FIG. 6 (e) the generic communication channel602, strain sensors 604, and detector 600 of the generic straindetection feedback system shown in FIG. 6 (a) are embodied as the fiberoptic communication channels 622 and 626, displacement sensors 624, andan optical detector 620 and illumination source 628 respectively.

This embodiment functions in a similar manner to the generic functioningof a strain detection feedback system depicted in FIG. 6 (b) where thesent signals 603 are being altered by the sensors 604 and sent back asreturn signals 605 to the detector 600 along the communication channel602. It follows then that the communication channel 602, strain sensors604, detector 600, signal 603, and return signal 605 of a generic straindetection feedback system are embodied as a fiber optic channels 622 and626, displacement sensors 624, optical detector 620, optical source 628,an optical input signal, and a reflected input signal respectively inthe system shown in FIG. 6 (e).

Electrical Strain Detection Feedback Systems

In addition to optical fiber based strain detection feedback systemsthere exists other forms of strain detection feedback systems that maybe used to detect strain or faults within a tissue phantom. A commonexample of such a system is an electrical circuit based system such asthe system depicted in FIG. 7 (c). Two exemplary electrical system mayemploy simple ammeter sensors or bonded strain gauge sensors such asthose shown in FIG. 12. FIG. 7 (c) shows a generic circuit diagram of anelectrical strain detection feedback system as it may be employed in anembodiment of the device as disclosed herein. In general an electricalstrain detection feedback system will have a voltage source 736 to powerthe circuit, electrical communication channels 734 to relay informationfrom the sensors 730, detectors (such as a computer or microcontroller)732 to interpret an acquired electrical signal from the sensors alongthe electrical communication channel, and a relative ground 740 as isrequired for all circuits to function.

In the first exemplary system the sensors 730 are simply connectionpoints at which the communication channels 734 connect to the ground 740of the circuit. When the connections exist current flows from thevoltage source 736 to the ground 740 through the communication channels734. The detector 732 is an array of ammeters measuring the current flowthrough each communication channel 734 and are connected to a computeror microcontroller programmed with instructions to provide an indicationof which communication channel has an error if any of the communicationchannel currents drop to zero while the voltage source 736 is on. Thusif a connection is broken, for example through the application of excessstrain, the microcontroller will provide information as to which sensorwas damaged.

It should be noted that all of the electrical communication channels maybe oriented along a single electrical cable with a single ground wire oralong individual electrical communication channel cables each with theirown ground. If the location of the sensors are known along the length ofthe electrical communication channel than when an indication is providedthat an error has occurred along that channel the location of whichchannel has been damaged will indicate where excess strain was applied.However if the current of a group off successive electricalcommunication channels drops to zero and the channels are oriented in asingle cable than it may be probabilistically assumed that the channelthat the connection that broke was that of the sensor closest to thedetectors 732 when the system is oriented in the manner shown in FIG. 7(c). This results from the sensors 730 being essentially in a serialorientation thus if a lower connection is broken all of the higherconnections will be broken as well. This particular embodiment althoughuseful provides no information as to the magnitude of the strain beingapplied at the point of interest.

The alternate electrical strain detection feedback system embodiment mayuse electrical bonded strain gauge sensors in place of the connectionbased sensors as described above. An example of such a sensor is shownin FIG. 13 (a) [Starck, Jason. “Strain Gauges.” All About Circuits ForumRSS. N.p., 2014. Web. 13 Nov. 2014]. Bonded strain gauges take advantageof the inherent relationship between the resistance of an electricalconductor and the strain being applied to it. Referring to FIG. 13 (a)as the bonded strain gauge 1300 is exposed to compression or tensionalong its long axis the electrical conductor increases and decreases inlength effectively changing its resistance.

The change in voltage caused by the change in resistance may then bemeasured and correlated with the change in strain. This embodiment isalso illustrated in FIG. 7 (c) the only difference being this embodimentwould not require the ammeters 732 hence why they are shown with dashedlines, indicating they are removable. When being used to illustrate thisembodiment the sensors 730 in FIG. 7 (c) may be any circuits employingstrain gauges, such as the one depicted in FIG. 13 (a), utilized in theform of a sensor to output the strain felt at the location of thesensor. Such a sensor may take the form of the circuit shown in FIG. 13(b). In the figure two strain gauges 1300 are employed, one may belocated on the wire while the other is used to compensate for anytemperature related strain response. As strain is detected by the straingauge on the wire the voltage change caused by the increased ordecreased resistance of the electrical strain gauge may be measured bythe voltmeter 1308 and output to a microcontroller (not shown). Thisoutput may then be converted to a strain reading by the equationprovided below and be communicated to the user.

$ɛ = \frac{4v}{{BV} \cdot {GF}}$

Where ε is the strain, v is the voltage read across the bridge of thecircuit by the voltmeter 1308, BV is the bridge excitation voltageprovided by the source 1304, and GF is the gage factor. It should benoted that the voltage source of the sensor circuit 1304 and ground 1306in FIG. 13 (b) may be the same as the voltage source 736 and ground 740of the diagram in FIG. 7 (c). This voltage source and ground may also becommon across all sensors (SEN: 1 . . . SEN: 6) in the strain detectionfeedback system shown in FIG. 7 (c).

Polarization Maintaining FBG and Photonic Crystal Fiber DetectionFeedback Systems

In addition to the examples described above employing fiber opticchannels, many types of optical fiber channels may be utilized. Thesealternative optical fiber channels may be used in combination with or tosubstitute for the fiber optic channels of the previous examples whereapplicable.

Presently FBGs may be integrated into many different optical fibers withthe most common ones being single mode and multimode. Some advantages ofutilizing single mode fibers include providing optimal lighttransmission and reflection with the least intensity loss whileadvantages of utilizing multimode fibers include a large bandwidth forwavelength multiplexing configurations, such as described in detailabove.

In addition, FBGs may be made in specialty fibers, including but notlimited to polarization maintaining fibers and photonics crystal fibers.Polarization maintaining fibers are optical fibers that allow twoorthogonal linearly polarized light beams (of the same or differentwavelength) to be propagated and maintained over the entire fiber opticchannel length with little or no cross-coupling of optical power betweenthe two orthogonal channels. Polarization maintaining fibers maintainpolarization by introducing stress in the fiber core via a non-circularcladding cross-section, or via rods of another material included withinthe cladding. For example, an elliptical cladding could be used toinduce stress in one direction while inducing little or no stress in theorthogonal direction. This essentially creates two orthogonallypolarization channels with different refractive indices As a result,each polarization channel may maintain a linearly polarized light beam.In another example, circular or trapezoidal stress rods may be added inthe cladding to add stress in only one direction of the fiber, namelyPanda Polarization Maintaining fibers and Bow-Tie PolarizationMaintaining fibers. Due to the strong birefringence created in thepolarization maintaining fiber optic channel by the induced stress,linearly polarized light maintains its polarization state throughout theentire propagation length of the fiber optic channel with little or noperturbation by stress, strain, and temperature fluctuation within thefiber and its surrounding environment.

By integrating FBGs into polarization maintaining fibers, two orthogonalpolarization modes in the polarization maintaining fiber optic mayreflect at different wavelengths since the effective refractive indicesfor the two modes are different as a result of the inducedbirefringence. In each channel, the Bragg wavelength shift induced by astrain change is generally similar to that for a fiber Bragg grating ina single mode fiber. The Bragg wavelength λ_(i) in polarizationmaintaining fiber is obtained using:λ_(i)=2n

(i=X,Y).

The advantage of having two orthogonal polarization channels built intoa single fiber optic channel is it allows multi-axis strain andtemperature sensing. FIG. 14 (a) shows an example strain sensing systemin which two detectors and a polarization beam splitter are used todetect the two orthogonally polarized channels in the polarizationmaintaining fiber optic channel. The reflectivity and wavelength shiftchanges with the angle of applied load in addition to the strain level.FIG. 14 (b) shows how the wavelength shifts in each polarization channelwith respect to the angle and pressure level from as shown in the paper[C. M. Lawrence et al., “A Fiber Optic Sensor for Transverse StrainMeasurement,” Experimental Mechanics 39 (3), 202 (1999)]. Anotheradvantage of using polarization maintaining fiber optic channel basedFBGs is the reduced perturbation to fiber bending and temperaturefluctuations at locations where fiber Bragg gratings are not writtenthus enabling strain sensing to be more accurate, sensitive and morelocalized to the sensing locations. Furthermore, the previouslydescribed multiplexing techniques may also be used with polarizationmaintaining fiber optic channel based FBG strain detection feedbacksystems.

Fiber Bragg grating could also be integrated with polarizationmaintaining photonic crystal fiber channels. Photonic crystal fiberchannels, also known as micro-structured optical fibers, photonicbandgap fibers, and holey fibers, are optical fiber channels where lightconfinement and guidance is carried out using a periodic array of airholes (i.e. photonic crystals) instead of a solid cladding as done inthe polarization maintaining fiber optic channel mentioned above. Theperiodic array of air holes creates an optical bandgap in the claddingthat prevents selected bands of frequencies from escaping the core; thusconfining a light beam within the photonic crystal fiber core.Additional polarization maintaining features may also be added tophotonic crystal fibers in a similar way to polarization maintainingfibers in which rods of a different material or additional holes couldbe added along one axis to create two channels with different effectiverefractive indices. The shifted wavelength Δλ in polarizationmaintaining fiber based fiber Bragg grating is obtained usingΔλ=2B

  (2)where B is the stress-induced birefringence, and

is the period in the fiber Bragg grating. The birefringence is relatedto differential stress by:B=(C ₁ −C ₂)(σ_(x)−σ_(y))  (3)where C₁ and C₂ are the stress-optic coefficients of the fiber materialwhich are silica in photonics crystal fibers. The values of C₁ and C₂are −6.9×10⁻¹³ and −41.9×10⁻¹³ m²N⁻¹ respectively [Y. Yang et al., “Anembedded pressure sensor based on polarization maintaining photoniccrystal fiber,” Measurement Science and Technology 24, 094004 (2013)].σ_(x), σ_(y) are the induced stresses in the orthogonal directions. FBGsintegrated into photonic crystal fibers demonstrate enhanced sensitivityfor strain sensing compared to conventional single mode fiber Bragggrating [H. V. Thakur et al., “Polarization maintaining photonic crystalfiber sensor embedded in carbon composite for structural healthmonitoring,” Measurement 44, 847 (2011)]. Moreover, these fibers aretypically made of pure silica which makes them relatively insensitive totemperature which may be useful in mock operations where temperaturechanges are not the primary metric to be measured. The wavelength shiftin these fibers is also very linearly with applied pressure andtemperature. FIG. 14 (c) shows an example of wavelength shifts versustransversal applied pressure and temperature from [Y. Yang et al., “Anembedded pressure sensor based on polarization maintaining photoniccrystal fiber,” Measurement Science and Technology 24, 094004 (2013)].Previously described multiplexing techniques could also be used withphotonic crystal fiber based fiber Bragg grating.Combination of Strain Detection Feedback Systems

In addition to the embodiments of strain detection feedback systemsdescribed above any combination of strain detection feedback systems maybe employed to improve the effective capability of any individualsystems. Two examples of such embodiments are provided in FIGS. 15 (a)and (b). The first block diagram FIG. 15 (a) shows an FBG based straindetection feedback system employing wavelength division and timedivision multiplexing. This system functions in the same manner as atime division multiplexed system where in addition to interrogating thereflected input signal for which time range it falls within it is alsointerrogated for what wavelength band it falls within (this may requirethe use of an external computer or microcontroller). The wavelength ofthis reflected input signal will be the altered Bragg wavelength of theFBG sensor. The detector may then analyze this reflected input signal todetermine its wavelength (or range of wavelengths). Following thisdetermination the time range may be used to assign the reflected inputsignal to a specific FBG sensor group (FBG: Xa, FBG: Xb, FBG: Xc).Following determination of the sensor group the specific sensor in thegroup (i.e. FBG: 1 y . . . FBG: 6 y) may be determined by the wavelengthband the reflected input signal falls in. Once assigned a specific FBGsensor (FBG: 1 a . . . FBG: 6 c) the following equation may be used todetermine a strain value corresponding to the reflected input signal.

$ɛ = {\frac{\lambda_{BS} - \lambda_{BO}}{\lambda_{BO}\left( {1 - P_{e}} \right)} - \frac{\left( {\alpha_{\Lambda} - \alpha_{\eta}} \right)\Delta\; T}{\left( {1 - P_{e}} \right)}}$

Where λ_(BO) is the original Bragg wavelength of the assigned FBGsensor, λ_(BS) is the wavelength of the reflected input signal and ΔT isthe change in temperature at the FBG. The assigned FBG sensor along withthis calculation then provides information as per the amount of appliedstrain and the location of that applied strain (i.e. a specific sensor704).

The second block diagram FIG. 15 (b) shows a combination of anelectrical, wavelength, and spatial division multiplexed straindetection feedback systems. To further clarify the block diagram showsan FBG based wavelength division multiplexed system spatiallymultiplexed with an electrical based strain detection feedback system.These individual systems work with the same principles used above wherethe spatial division multiplexing is used to combine the two otherstrain detection feedback systems with a single detector (which may beformed of multiple microcontrollers or computers). This system is simplyan aggregation of parts with a common detector 1500 used to spatiallymultiplex the parts as opposed to the embodiment shown in FIG. 15 (a)which is a composition of systems. Regardless of this differentiationeither combination may be used to improve the functioning of such straindetection feedback systems.

It should be noted that any of the sensors 604 of the strain detectionfeedback systems as described may also be implemented with wirelesscommunication channels (i.e. communication channel 602 may be wireless)where possible as opposed to the non-wireless communication channels asdescribed.

Shape Sensing Detectors Aligned Anatomically in a Spinal Phantom

In addition to the brain tissue phantom embodiment described aboveanother embodiment of the tissue phantom device as disclosed hereinwould be a spinal tissue phantom as shown generally at 1680 in FIG. 16.In this embodiment 1680, the artificial ligaments, nerves, andintervertebral discs may be formed in entirety or in part of feedbacksystem(s) monitoring particular metrics of the artificial tissue beingreplicated.

When integrating feedback systems in the tissue phantom device 1680 asdisclosed herein in some embodiments it may be advantageous to use thephysical hardware (i.e. parts) of the feedback systems to mimic actualanatomies contained within or on the specific anatomy being replicatedby the tissue phantom device. This mimicry may take the form ofanatomical properties, anatomical shapes, anatomical locations, and etcthat will be described further as follows.

Referring to FIG. 16 in the embodiment 1680 the artificial SupraspinousLigament 1610 may be formed of a fiber optic channel with claddinghaving a similar elastic module to that of the ligament to mimic itsproperties. This fiber optic channel may also be located in a positioncorresponding to where this Supraspinous Ligament 1610 is located in anactual patient anatomy to mimic its anatomical location. In addition thefiber optic channel may be formed of multiple channels each chosen tohave a radius similar to that of the muscle fibers that form thisSupraspinous Ligament 1610 to closely mimic the shape of it. Thus when amock medical procedure is performed on the spinal tissue phantom thisartificial Supraspinous Ligament 1610 will respond in a similar way toan actual Supraspinous Ligament 1610 and because it is formed of a fiberoptic channel it may also simultaneously provide feedback metrics.

The fiber optic hardware used to form the Supraspinous Ligament 1610 inthis embodiment may be integrated with any of the feedback systems asdescribed herein which employ a fiber optic channel. Some examplefeedback systems may be the FBG, ODTR, or ODFR (below) feedback systemsemploying fiber optic channels as described herein, or any otherfeedback systems described herein or applicable for use with the fiberoptic cable. It should be noted that when using the feedback systemhardware to mimic the actual anatomy being replicated that theanatomical properties, anatomical shape, or the anatomical location maybe mimicked individually or in any combination thereof. In additionthese anatomical characteristics that may be mimicked are provided asexamples only and should not be taken as limiting other possibleanatomical characteristics which may be mimicked.

Also when integrating feedback systems in the tissue phantom device 1680as disclosed herein in some embodiments it may be advantageous to mapspecific sensor characteristics to specific anatomical volumes ofinterest. For example when employing intensity division multiplexing incombination with spatial division multiplexing it may be advantageous tosegregate the fiber optic channels being multiplexed by wavelength suchthat each wavelength may correspond to a different anatomical part ofthe tissue phantom device as disclosed herein. This is shown in thespinal tissue phantom device embodiment in FIG. 16 where each type ofanatomical part formed with the spatially multiplexed fiber opticchannels as described are differentiated from the other anatomical partsbased on their input signal wavelength.

In FIG. 16 the Supraspinous Ligament 1610 is identified with an inputsignal wavelength range corresponding to a first color, the Inter-SpinalLigament 1620 is identified with an input signal wavelength rangecorresponding to a second color, the spinal nerve 1640 is identifiedwith an input signal non-visible wavelength, the annulus of theintervertebral discs 1630 are identified with an input signal wavelengthrange corresponding to a third color, and the Posterior LongitudinalLigament 1600 is identified with an input signal wavelength rangecorresponding to a fourth color.

In some embodiments it may also be advantageous to register thelocations of the feedback systems hardware (such as sensors) with thetissue phantom device as disclosed herein so as to know exactly wherethe feedback is originating from. For example in an embodiment where thefeedback system hardware is chosen to mimic major fiber tracts in thebrain phantom shown in FIG. 27 such as the optical tract 2700 it isadvantageous to know where these major nerve bundles are such that asurgeon may avoid them similar to when they perform an actual surgery.Thus when performing a mock procedure such as a tumor resection if theseareas are affected (as per the metric provided by the feedback system)the training surgeon may alter their trajectory for the real surgerythey are preparing for. In an alternate embodiment the SupraspinousLigament 1610 and Posterior Longitudinal Ligament 1600 shown in FIG. 17may be initially placed in a known orientation and provided to thesurgeon. These two ligaments may then be produced with an integratedshape sensing feedback system that may provide feedback to a user of thespinal tissue phantom during a mock procedure as to the shape of thespine. This type of shape sensing feedback system may be advantageousfor use in some embodiments of the tissue phantom as disclosed herein asit provides dynamic movement information about the mock anatomy duringthe mock medical procedure.

It is a common occurrence in spinal surgery for the vertebrae of thepatient to move relative to one another during a surgical procedure asthey are shaped to naturally do so such as shown by arrow 1700 in FIG.17. Thus knowing the initial orientation of the spinal tissue phantom1680 and being able to track its shape using a shape sensing feedbacksystem will allow for the replication of such an occurrence in a mockprocedure to occur and also allow for the training surgeon todynamically track the positioning and shape of the spine during saidmock procedure. This may assist training surgeons improve their skilland account for unexpected conditions during actual spinal surgeries. Anexample of such feedback systems would be a shape sensing detectionfeedback system that may be used to monitor the movement of thevertebrae relative to one another during a mock medical procedure. Theshape sensing sensors may take the form of optical fiber cables or asuitable tissue like material embedded with or incased within an organicflexible strain gauge array which will be described in further detailbelow in the descriptions of FIGS. 18 (i) and (ii).

FIG. 18 (i) shows a diagram depicting a shape sensing fiber optic cable1820. The cable contains a central fiber optic channel 1800 surroundedradially by three additional fiber optic channels 1810 each extending ina helical configuration along the length of the cable 1820 and aligned120° apart from one another. Optical Frequency Domain Reflectometry(OFDR) is used to interrogate each fiber optic channel and determine thedistributed strain amplitude of each fiber optic along the length of thecable 1820. When the cable is deformed in a curve configuration theradial cores undergo alternating states of tension and compressionthrough the region of the curve. An example of a strain response 1830 ofthis cable on an interval having a typical curvature is shown in FIG. 18(a). The magnitudes and phases of these strain responses along withknowledge of their relative location to one another at a specificdistance in the cable may then be used to infer the magnitude anddirection of curvature of the shape sensing cable. A furtherclarification may be found in the paper [Luna Innovations Inc.; FiberOptic Shape Sensing, Current State of Technology: Publisher, Jun. 21,2013].

FIG. 18 (ii) shows a diagram depicting a shape sensing strain gaugearray 1840. The strain gauges in this array work analogously to thestrain gauges described above. The figure depicts individual straingauges 1850 on a flexible substrate 1860. This flexible substrate 1860works as a circuit board carrying signals to and from an interrogationcircuit (such as contained within a microcontroller (not shown) forexample) that may infer the shape of the entire body of the array basedon the strain readings of individual sensors. This can be accomplishedby mapping the individual strain gauges to a virtual model of the shapesensing strain gauge array or other applicable means. In order to inferthe shape of the array the signals may be encoded depending on thelocation of the sensor. As the strain gauge shape sensing device isflexed 1880 the individual sensors 1850 are strained accordingly such assensor 1870 on the right hand side of FIG. 18 (ii).

Alternative Surgical Metrics

During mock surgical interventions with tissue phantoms alternativefeedback metrics in addition to the strain measurements as described indetail above may also be significant in providing information as to therelative success or progression of a mock surgical operation. Referringto FIGS. 19 and 20 for example during port based medical proceduresbipolar forceps 1900 are commonly used to cauterize bleeding vessels1920 yet the thermal damage 2000 (best seen in FIG. 20) caused by thistool 1900 is hard to determine at times and may never be determinedduring an actual surgery. In yet another example functional stimulationis commonly performed in or on the surface of the brain, and whenconducted on the surface, any thermal damage may or may not be visible,but when conducted in the depth of the brain where only a probe can gainaccess, the damage will not be apparent until either the patientconsciously notices a difference in their ability to function or thedamage is imaged.

There are also medical procedures that attempt to damage unwanted tissueand remove it. For example a method of removing tissue involvesradiation therapy wherein high doses of radiation are applied to an areacontaining a tumor in order to damage the desired tissue so the body mayautonomously remove it.

These feedback metrics although difficult to determine during an actualmedical procedure may be rendered determinable in a mock procedure giventhe tissue phantom device as disclosed herein is employed. Thus suchmetrics may improve a training surgeon's ability to better predict thelimits of their intervention in order to produce desirable results.Without such a training tool it may be otherwise difficult to estimatewithout extensive practical experience causing trauma to actualpatient's livelihoods.

One way to produce such a feedback metric would be to create a tissuephantom of a matrix in its entirety or at least partially such that ithas inherent characteristics that would cause the matrix properties tochange as a result of exposure to the applicable interventionaltherapies such as heat from an electrocautery tool, electrical currentfrom a functional stimulation tool, or radiation from a radiationtherapy tool (such as, but not limited to, a gamma knife). Tissuematerials that may exhibit these properties will be described furtherbelow.

Thermally/Optically Reactive Material

In an embodiment, for example the tissue phantom device 2212 shown aspart of the tumor resection procedure depicted in FIGS. 19 and 20, athermally activated crosslinker may be suspended in the targeted volume1950 (or the entire volume 2212) of the tissue phantom device 2212. Thisthermally activated crosslinker when exposed to an increasedtemperature, for example at the cauterization end of the electrocauterytool 1900 could activate a crosslinking reaction between polymer chainscausing an increased rigidity at the targeted volume, shown as thesub-sectional volume 2000 of the targeted volume 1950 in FIGS. 20 (a)and 20 (b).

Once the mock procedure has been completed a comparison of the denservolume with the planned mock volume which was to be operated on may bedone to provide a feedback metric to the training surgeon as to thelevel of success of the performed mock procedure. The denser volume maybe acquired through processes such as but not limited to, dissecting thetissue phantom device and removing the denser area, imaging the tissuephantom device, or performing a biopsy on the device.

Furthermore in an alternate embodiment of the tissue phantom device 2212shown as part of the mock tumor resection procedure depicted in FIGS. 19and 20, may be produced of a hydrogel material. If then a heatedelectrocautery instrument 1900 was applied near the area 1950 by atraining surgeon the hydrogel in the region 2000 may cause a change inwater content (due to evaporation) and consequently the density in theregion 2000. This would result in a measurable feedback metric analogousto that provided by the crosslinker material mentioned above.

In an example, using a hydrogel based material, the change in watercontent of the hydrogel as a response to the heat emanated by acauterization could modulate the density of the hydrogel in the targetedzone, causing a measurable effect.

In a second embodiment, a solid material with a melting rangecommensurate with the temperature reached by the applicable probe suchas the electrocautery tool 1900 shown in the tumor resection procedurein FIGS. 19 and 20 may be incorporated into the target volume 1950 or asshown in the figure the entire volume of the tissue phantom 2212. Onmelting during a treatment, loss of this material and the extent of theresulting rheological change could be used as a feedback metric for thelevel of success of the mock procedure. Again once a mock procedure hasbeen completed the amount of matrix that had been melted may be used asan indicator of success of the surgery. And again the melted volume maybe determined through processes such as but not limited to, dissectingthe tissue phantom device and removing the denser area, imaging thetissue phantom device, or performing a biopsy on the device.

In an alternate embodiment an electrochromic material may be used inplace of the material with a melting point commensurate with thetemperature reached by the applicable electrocautery tool during acauterization of a tissue. The electrochromic material would changecolor (temporarily or permanently) depending on the voltage applied thusproviding a feedback metric to the training surgeon using the tissuephantom device as disclosed herein. Using a reversible electrochromicmaterial may be advantageous for use in the mock tumor resectionprocedure mentioned a priori as the damage caused by the electrocauterydevice would be seen immediately by the training surgeon which wouldallow them to change their use of the device throughout the remainingsurgery to cause less damage.

In an alternate embodiment employing a reversible electrochromicmaterial it might be advantageous to form the tissue phantom of atranslucent material surrounding the target volume (such as 1950 asmentioned above). This target volume would contain the suspendedelectrochromic material. The translucency of the tissue phantom wouldfacilitate the change in chromaticity of the material to be more easilyobserved by the training surgeon. This may also potentially allow thetissue phantom to be preserved in scenarios where the phantom wouldotherwise be dissected. Some non-limiting examples of electochromicmaterials may be some of the transition metals as mentioned in the paper[Somani, Prakash R., and S. Radhakrishnan. “Electrochromic materials anddevices: present and future.” Materials Chemistry and Physics 77.1(2003): 117-133.]

Tool Integrated Phantoms

Feedback metrics such as those mentioned above are helpful for improvinga training surgeon's ability in reducing damage to unwanted regions of atissue phantom however there are also advantages in having detectionmetrics which are directly dependent on the training surgeons (or otherusers) interventional movements with their tool. For example duringcortical mapping of the brain it is common for a surgeon to use astimulation probe such 2100 shown in FIG. 21 to stimulate particularwhite matter tracts to confirm there function and location. Whenperforming tumor resection surgeries it is common for a surgeon to planto avoid particular tract bundles to minimize trauma to the patient. Inanother example when faced with vasculature in or around a volume ofunhealthy tissue in the brain to be removed, it is common for a surgeonto strip the vasculature with a suction tool, if it is an importantartery or vain. In yet another example during deep brain stimulation(DBS) procedures surgeons commonly employ a microelectrode recordingtool to confirm the DBS probe has reached the target location (in mostcases the STN) by listening to the induced current in the probe. Thereare many embodiments which may be employed in the tissue phantom deviceas disclosed herein as will be further discussed as follows.

To better facilitate a mock cortical mapping exercise for a trainingsurgeon, an embodiment of a mock tissue phantom device as disclosedherein may be produced with artificial functional tracts that mayprovide metrics reflective of functional stimulation responses. Anexemplary embodiment of such a tissue phantom device is provided in FIG.21. The left side of the figure depicts the sulci of the brain 2102(through the mock craniotomy 2106 and mock skull 2104) and a stimulationprobe 2100 inserted through one of the sulci 2102 into the brain phantom2112. The right side of the figure shows the internal structurescontained within the brain phantom matrix material. These internalstructures 2108 replicate the tractography of the brain. Based oninteraction with the functional stimulation probe 2100 the artificialbrain tracts 2108 may provide information reflective of a functionalstimulation response of a real fiber tract of a brain.

The artificial brain tracts shown in FIG. 21 are conductive cableswherein each separate segment of tractography 2108 is a separateconducting cable. The conducting cables are connected to a central cable2110 that runs them to the ground of the voltage source 2114. Thestimulation probe 2100 in FIG. 21 is connected to the positive end ofthe voltage source. A computer 2116 is connected to the voltage source2114 which may determine which artificial tracts cable 2108 isstimulated if the stimulation probe makes contact with one of theartificial tracts during a mock cortical mapping procedure. This can beaccomplished simply by measuring the current running through each of theartificial tractography cables 2108.

It should be noted that there is enough inherent resistance along any ofthe artificial tractography cables 2108 to allow for an electricalcurrent to flow through them. The computer 2116 may then provideinformation as to which tract has been contacted by the stimulationprobe. The exemplary embodiment of a mock tissue phantom as shown inFIG. 21 thus allows for a surgeon to perform a mock cortical mappingexercise with additional knowledge of what tracts they may bestimulating. This may improve a training surgeon's ability to accuratelyreach the target tractography in a patient's brain during an actualprocedure, especially if the artificial tractography 2108 and brainphantom surface mimic the tractography and surface of an actualpatient's brain.

To better facilitate a mock DBS procedure exercise for a trainingsurgeon, an embodiment of a mock tissue phantom device as disclosedherein may be produced with an artificial STN (Sub thalamic Nucleus)that may provide metrics reflective an STN response. Two exemplaryembodiments of such a tissue phantom device are shown in FIGS. 22 and23. Common to both embodiments is a mock skull 2104 and internal brainphantom 2212 through which a (mock or actual) MER (Microelectroderecording) device 2200 is being advanced along a trajectory towards atarget, in this case the mock STN 2202. In the first embodiment shown inFIG. 22 an EM field generating module 2205 is connected through a cableto the center of the mock STN where an EM field generator transmitterprobe (such as a battery powered solenoid) is then used to induce an EMfield similar to that produced by an STN when implanting a DBS probeduring actual DBS procedures. As is a common occurrence in the field theSTNs EM field may be stronger in a closer vicinity to the STN such asthat shown by the dashed line boundary 2208 and weaker further away suchas on the boundary shown by dashed line boundary 2211.

The MER device 2200 in this case may be an actual device to betterreplicate the DBS procedure. The MER device 2200 is connected to an EMfield detector 2213 module and the device itself contains an EM fielddetector. This EM field detector module 2213 will then relay thedetected EM field as an audible signal through a speaker 2216 that maybe used by the training surgeon to determine where the tool 2200 is inthe mock internal brain phantom 2212 (i.e. where the tool may berelative to the vicinity of the STN 2202).

The embodiment shown in FIG. 23 is analogous to the embodiment shown inFIG. 22 in that mock procedure may be performed in the same manner onlythat the EM field would be replaced by a photon intensity flux through adiffusing medium and the MER device would be in the form of an opticalluminous intensity detector to detect the strength of the photon flux atvarious locations in the internal brain phantom 2212. In this embodimentthe tissue phantom containing the mock STN is made of a translucentmaterial that diffuses (scatters) photons as opposed to absorbing them.In this embodiment the STN 2202 is also constrained to be a photondiffusing material, for better replication of an actual DBS procedure itwould be desirable to have the STN 2202 be transparent such that anyincoming light would pass through it and only begin diffusing into theinternal brain phantom material 2212 surrounding it. This would becloser to the EM field of an actual STN as it is for the most partconsistent throughout the STN and only begins to reduce outside of it inthe brain. The light source module 2316 in this embodiment is equivalentto the EM field generator module 2205 in the embodiment shown in FIG.22. Similarly it is routed to the mock STN 2202 through a channel (fiberoptic in this case) and is emitted in the STN where it will create aphoton flux field around the STN 2202 and a strong substantiallyconsistent photon flux field within the STN 2202.

As is a common occurrence in the field, the STNs equivalent photon fluxfield may be stronger in a closer vicinity to the STN such as that shownby the boundary 2310 and weaker further away such as on the boundaryshown by 2308. In this embodiment the MER device 2200 is connected to anoptical detector module 2314 and the device itself contains a light pipeto transfer photons to the optical detector module 2314 to be detected.This optical detector module 2314 will then relay the detected photonintensity as an audible signal through a speaker 2216 that may be usedby the training surgeon to determine where the tip of device 2200 is inthe mock internal brain phantom 2212 (i.e. where the tip of device 2200may be relative to the vicinity of the STN 2202).

To better facilitate a mock tumor resection exercise for a trainingsurgeon, an embodiment of a tissue phantom device as disclosed hereinmay be produced with artificial functional tracts that may providemetrics reflective of tractography damage. An exemplary embodiment ofsuch a tissue phantom device is provided in FIGS. 24 to 27. Thesefigures show the progression of a commonly performed port based tumor(not shown) resection with two simultaneous views of the internalstructures and external form of the tissue phantom. FIGS. 24 (a) and 24(b) shows the mock surgery before an access port 100 is inserted into asulcus 2400 of the mock brain 2212, FIGS. 25 (a) and 25 (b) show theaccess port during cannulation to the bottom of the sulcus 2400, andFIGS. 26 (a) and 26 (b) show the access port 100 after it has penetratedthe bottom of the sulcus 2400 as it is being advanced to the target.

In an embodiment the artificial tracts 2410 (FIG. 24 (b)) may be in theform of fiber optic channels wherein a light source (not shown) mayinject light of any wavelengths into the channels. If one of the fiberoptic channels representative of an actual brain tract is then broken,such as fiber 2600 in FIG. 26 (b), it would release light indicating theartificial tract had been damaged. In order to allow the released lightto be observed outside the artificial brain 2212 material it would beadvantageous for the artificial brain 2212 to have a translucentcharacteristic such that the released light may diffuse into thematerial and be seen by the training surgeon practicing the exercise.Another manner in which the released light may be communicated to thesurgeon would be through the use of a photochromic material such as thatdescribed in the embodiment above. In an embodiment specific groups oftracts may be injected with specific wavelengths of light indicative ofthe tract type as shown in FIG. 27. For example the tracts 2410 shownradiating out from the central tract 2420 correspond to the CoronaRadiata and may be chosen to be represented by light with a specificwavelength range potentially corresponding to a specific color such asyellow.

In another example the optical tract may be chosen to be represented bylight with a specific wavelength range potentially corresponding to aspecific color such as blue. In an alternate embodiment the fiber opticchannels may be representative of vasculature in the brain. This may beadvantageous in that a surgeon training to strip vasculature in a volumeof unhealthy tissue would be informed if they damaged the artificialvasculature and caused a bleed to occur. To implement this the wires ofstrain detecting feedback system shown in FIG. 7 (c) and described abovemay be used as the vasculature. In an embodiment this artificialvasculature would ideally have the same material properties as actualvasculature. For example, toughness, modulus of elasticity, hardness,etc. similar to the fiber optic channel used to form the SupraspinousLigament as described above.

In an alternate embodiment of the tissue phantom device shown in FIGS.24 to 26 the strain detection feedback system shown in FIG. 7 (c) may beemployed where each of the electrical communication channels 734 maycorrespond to a tract 2410. Thus if any of the tracts are damaged thesurgeon may be informed by the microcontroller. This embodiment may notrequire the artificial brain 2212 material to have any specificproperties like the previous embodiment.

The sensorized phantoms disclosed herein may be generic phantoms usedsimply for training purposes. In addition, the phantoms may be patientspecific phantoms, produced based on preoperative imaging of theanatomical part of the patient undergoing the medical procedure. Thus ifa patient has a brain tumor, preoperative imaging of the patient's brainmay be used to construct a lifelike brain phantom including the tumor,with the brain structures and tumor being made of material selected tomimic the biomechanical properties of the brain structures and tumor.This phantom will give the clinician an opportunity to practice themedical procedure in a very realistic manner.

It should be noted that it is advantageous to orient any strain sensorsand artificial tracts or other artificial anatomical parts with built insensors in a manner consonant with human anatomy. It is alsoadvantageous to have these artificial anatomies designed with propertiesas similar to the actual anatomies being mimicked as possible.

It should be noted that any of the surgical exercises employing thetissue phantom device embodiments as disclosed herein should notconstrued as limiting the use of the tissue phantom device to just thoseexercises and are given as examples to assist in understanding thetissue phantom device only.

While the Applicant's teachings described herein are in conjunction withvarious embodiments for illustrative purposes, it is not intended thatthe applicant's teachings be limited to such embodiments. On thecontrary, the applicant's teachings described and illustrated hereinencompass various alternatives, modifications, and equivalents, withoutdeparting from the embodiments, the general scope of which is defined inthe appended claims.

Except to the extent necessary or inherent in the processes themselves,no particular order to steps or stages of methods or processes describedin this disclosure is intended or implied. In many cases the order ofprocess steps may be varied without changing the purpose, effect, orimport of the methods described.

What is claimed is:
 1. A sensorized tissue phantom for performing a mocksurgical procedure, comprising: a tissue phantom mimicking an anatomicalpart, the tissue phantom comprising at least one sensorized portionconfigured to provide feedback metric when said at least one sensorizedportion is interacted during a mock surgical procedure, said at leastone sensorized portion comprising at least one sensor, the at least onesensor comprising a sensing material, the at least one sensing materialmimicking tissue as a part of the tissue phantom, the at least onesensing material mimicking at least one of directionality, density, andelasticity of the tissue, and the sensing material comprising at leastone electromagnetic radiation source and at least one of: at least onefluorophore, at least one photo-reactive material, at least onethermally-reactive material, at least one electrochromic material, andat least one radiochromic material, wherein the at least oneelectromagnetic radiation source is embedded in, and in close proximityto, a preselected portion of said tissue phantom corresponding to apreselected anatomical section of said anatomical part; and a detectorconfigured to detect electromagnetic radiation signals emitted by the atleast one electromagnetic radiation source.
 2. The sensorized tissuephantom of claim 1, wherein said at least one sensorized portionrepresents at least one of: at least one anatomical location, at leastone selected biomechanical property, at least one physical shape, and atleast one anomalous physiological structure undergoing the mock surgicalprocedure of at least one portion in said anatomical part.
 3. Thesensorized tissue phantom of claim 1, wherein the at least one sensorcomprises a plurality of sensors disposed in said at least onesensorized portion, wherein the plurality of sensors is distributedthroughout said at least one sensorized portion, wherein the pluralityof sensors is coupled with a communication channel, and wherein thedetector is coupled with the plurality of sensors by way of saidcommunication channel.
 4. The sensorized tissue phantom of claim 3,further comprising a computer processor coupled with said detector, saidcomputer processor programmed to visually display an output from eachsaid at least one sensor of the plurality of sensors.
 5. The sensorizedtissue phantom of claim 4, further comprising an audio alarm devicecoupled with said computer processor.
 6. The sensorized tissue phantomof claim 3, wherein said communication channel comprises at least oneoptical fiber, wherein said plurality of sensors comprises: a pluralityof Fiber Bragg gratings spaced along said at least one optical fiber anda light source coupled with said at least one optical fiber, and whereinsaid detector is configured to detect a spectral response from lightreflected by said plurality of Fiber Bragg gratings.
 7. The sensorizedtissue phantom of claim 3, wherein the communication channel comprisesan optical fiber, wherein the optical fiber is coupled with a lightsource, wherein said detector comprises an optical time domainreflectometer, and wherein said optical time domain reflectometerdetects a reflected light signal trace.
 8. The sensorized tissue phantomof claim 3, wherein said communication channel comprises at least oneelectrical wire, wherein each said at least one sensor of the pluralityof sensors further comprises at least one electrical strain gauge, andwherein said detector detects strain experienced by each said at leastone sensor of the plurality of sensors.
 9. The sensorized tissue phantomof claim 3, wherein said communication channel comprises at least oneelectrical wire, wherein each said at least one sensor of the pluralityof sensors further comprises an organic semiconductor strain gauge, andwherein said detector detects strain experienced by each said at leastone sensor of the plurality of sensors.
 10. The sensorized tissuephantom of claim 3, wherein, the sensing material comprises said atleast one fluorophore which is embedded in the tissue phantom, and theat least one optical fiber operates as the communication channel, andwherein the at least one optical fiber is coupled with at least onelight source, and the at least one light source configured to excite theat least one fluorophore embedded in the tissue phantom, such that, uponat least one condition of a breakage and a local bend, due to contactwith a given optical fiber, light is emitted into the tissue phantom toexcite the at least one fluorophore in close proximity to a location ofsaid condition.
 11. The sensorized tissue phantom of claim 1, whereinthe at least one sensor of the plurality of sensors represents at leastone of: an anatomical location, at least one selected biomechanicalproperty, at least one physical shape, at least one anomalousphysiological structure undergoing the mock surgical procedure of atleast one portion in said anatomical part.
 12. The sensorized tissuephantom of claim 1, wherein said detector comprises a probe insertableinto the preselected portion of said tissue phantom, and wherein saiddetector is configured to detect electromagnetic radiation from saidpreselected portion of said tissue phantom.
 13. The sensorized tissuephantom of claim 12, wherein said detector is coupled with an audiblespeaker, and wherein the audible speaker is configured to emit anaudible signal when said detector detects electromagnetic radiationindicative of a location said preselected portion of said preselectedportion of said tissue phantom.
 14. The sensorized tissue phantom ofclaim 1, wherein the sensing material is sensitive to selected stimuli.15. The sensorized tissue phantom of claim 14, wherein said sensingmaterial represents at least one of: an anatomical location, at leastone selected biomechanical property, at least one physical shape, atleast one anomalous physiological structure undergoing the mock surgicalprocedure of at least one portion in said anatomical part.
 16. Thesensorized tissue phantom of claim 14, wherein said sensing material,sensitive to selected stimuli, comprises at least one of: anelectrically sensitive material, a pressure sensitive material, anoptically sensitive material, a thermally sensitive material, aradiation sensitive material, and a sound sensitive material.